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The pattern of racial segregation in U.S. elementary and secondary schools has changed significantly over the last 25 years. This chapter examines the relationship between the racial composition of schools and the choices white parents make concerning the schools their children attend. Restricted access files at the Bureau of the Census allow us to identify each household's Census block of residence and, in turn, suburban public school districts and urban public school attendance areas. We find that the racial composition of schools and neighborhoods are very important in the school and location decisions of white families.

In this chapter we demonstrate the construction of inverse test confidence intervals for the turning-points in estimated nonlinear relationships by the use of the marginal or first derivative function. First, we outline the inverse test confidence interval approach. Then we examine the relationship between the traditional confidence intervals based on the Wald test for the turning-points for a cubic, a quartic, and fractional polynomials estimated via regression analysis and the inverse test intervals. We show that the confidence interval plots of the marginal function can be used to estimate confidence intervals for the turning-points that are equivalent to the inverse test. We also provide a method for the interpretation of the confidence intervals for the second derivative function to draw inferences for the characteristics of the turning-point.

This method is applied to the examination of the turning-points found when estimating a quartic and a fractional polynomial from data used for the estimation of an Environmental Kuznets Curve. The Stata do files used to generate these examples are listed in Appendix A along with the data.

Purpose – The purpose is to present item response theory (IRT) as a promising approach to deal with theoretical and methodological challenges which may not be adequately addressed with linear factor analysis (LFA) techniques.

Approach – We address this limitations and present IRT's approach to counteracting these difficulties. We further present two IRT models in greater detail and make a theoretical comparison between these models and LFA techniques. Then, we illustrate how IRT is applied in practice by analyzing a scale of trust by an IRT and an LFA approach and comparing their results.

Practical implications – Scale properties may vary among countries because some items may function differently in different contexts. Moreover, a scale's reliability depends on the value of the latent variable being assessed, which implies that the scale may discriminate better among certain ranges of the latent trait than among others. The theory we hereby present offers a more adequate approach to dealing with these issues than extant LFA methods.

Originality/value – This chapter presents a methodology of recognized value in other fields of knowledge into the field of strategy and international business, thereby advancing the methodologies available for doing research in these domains.

We study the correlates of immigrant location and migration choices to address the following questions: What location-specific, economic, and demographic factors are associated with these choices? Does the influence of these factors differ by immigrant characteristics? What are the factors associated with the observed increase in immigrant geographic dispersion during the 1990s? Our analysis suggests that: (1) There is significant heterogeneity in the correlates of immigrant location and migration choices; associations vary by immigrant birthplace, age, gender, education, and duration of residence in the United States. (2) Economic factors are, for the most part, weakly associated with immigrant location decisions. (3) Immigrants appear to be more attracted to states with large (growing) populations; less attracted to states with a high proportion of other foreign-born persons; more attracted to states with high unionization, and less attracted to states with high crime. (4) The association between location-specific characteristics and immigrant location choices changed between 1990 and 2000 for some immigrant groups and this explains most of the increase in geographic dispersion during the 1990s. In contrast, changes in location attributes and changes in immigrant composition explain relatively little of the increase in dispersion.

Purpose – The purpose of this chapter is to project the global emergence of megacities through the 21st century using population scenarios consistent with the Special Report on Emissions Scenarios (SRES) of the Intergovernmental Panel on Climate Change (IPCC).

Methodology – A dynamic urban growth model is developed based on a scale-independent theory of growing networks taking into consideration the geographical and climatic suitability of the location of cities. The model is able to generate a series of megacity projections consistent with an experimental city size distribution based on a national urban population scenario consistent with Zipf's law. The model is applied to population projections for 45,316 cities around the world using three population scenarios from SRES.

Findings – All of the projections indicate that a large number of megacities will be generated in developing regions towards 2100, although the range is wide and depends on the population assumed in the scenarios. Some results indicate an extreme population concentration in megacities; this might be undesirable for national security, quality of life, and sustainable development. Transport policies affect urban growth and national land development through changes in mobility and accessibility across the nation.

Implications – The results presented in this chapter could serve to stimulate discussions on urban and national transport policies and planning, particularly in China.

Purpose – The purpose of this chapter is to review the methodological and empirical underpinnings of transport network screening, or management, as it relates to improving road safety. As jurisdictions around the world are charged with transport network management in order to reduce externalities associated with road crashes, identifying potential blackspots or hotspots is an important if not critical function and responsibility of transport agencies.

Methodology – Key references from within the literature are summarised and discussed, along with a discussion of the evolution of thinking around hotspot identification and management. The theoretical developments that correspond with the evolution in thinking are provided, sprinkled with examples along the way.

Findings – Hotspot identification methodologies have evolved considerably over the past 30 or so years, correcting for methodological deficiencies along the way. Despite vast and significant advancements, identifying hotspots remains a reactive approach to managing road safety – relying on crashes to accrue in order to mitigate their occurrence. The most fruitful directions for future research will be in the establishment of reliable relationships between surrogate measures of road safety – such as ‘near misses’ – and actual crashes – so that safety can be proactively managed without the need for crashes to accrue.

Research implications – Research in hotspot identification will continue; however, it is likely to shift over time to both closer to ‘real-time’ crash risk detection and considering safety improvements using surrogate measures of road safety – described in Chapter 17.

Practical implications – There are two types of errors made in hotspot detection – identifying a ‘risky’ site as ‘safe’ and identifying a ‘safe’ site as ‘risky’. In the former case no investments will be made to improve safety, while in the latter case ineffective or inefficient safety improvements could be made. To minimise these errors, transport network safety managers should be applying the current state of the practice methods for hotspot detection. Moreover, transport network safety managers should be eager to transition to proactive methods of network safety management to avoid the need for crashes to occur. While in its infancy, the use of surrogate measures of safety holds significant promise for the future.

This paper introduces a behavioral framework to model residential relocation decision in island areas, at which the decision in question is influenced by the characteristics of island regions, policy variables related to accessibility measures, and housing prices at the proposed island area, as well as personal, household (HH), job, and latent characteristics of the decision makers.

The model framework corresponds to an integrated choice and latent variable (ICLV) setting where the discrete choice model includes latent variables that capture attitudes and perceptions of the decision makers. The latent variable model is composed of a group of structural equations describing the latent variables as a function of observable exogenous variables and a group of measurement equations, linking the latent variables to observable indicators.

An empirical study has been developed for the Greek Aegean island area. Data were collected from 900 HHs in Greece contacted via telephone. The HHs were presented hypothetical scenarios involving policy variables, where 2010 was the reference year. ICLV binary logit (BL) and mixed binary logit (MBL) relocation choice models were estimated sequentially. Findings suggest that MBL models are superior to BL models, while both the policy and the latent variables significantly affect the relocation decision and improve considerably the models' goodness of fit. Sample enumeration method is finally used to aggregate the results over the Greek population.

Measures are comparable if and only if measurement equivalence has been demonstrated. Although comparability and equivalence of measures are sometimes used interchangeably, we advocate a subtle but important difference in meaning. Comparability implies that measures from one group can be compared with measures from another group. It is a property of the measures, which is given or not. In particular, comparability presumes valid measures within each group compared. Measurement equivalence, by contrast, refers to the way measures are derived and estimated. It is intrinsically tied to the underlying theory of measurement. Thus, measurement equivalence cannot be dealt with in isolation. Its assessment has to be incorporated into the theoretical framework of measurement. Measurement equivalence is closely connected to construct validity for it refers to the way manifest indicators are related to the latent variable, within a particular culture and across different cultures. From this it follows that equivalence cannot, or should not, be treated as a separate issue but as a constitutive element of validity. A discussion of measurement equivalence without addressing validity would be incomplete.